In order to increase the flood resilience of cities (i.e., the ability to cope with flood hazards), it is also crucial to make critical infrastructure functions resilient, since these are essential for urban society. Cities are complex systems with many actors of different disciplines and many interdependent critical infrastructure networks and functions. Common flood risk analysis techniques provide useful information but are not sufficient to obtain a complete overview of the effects of flooding and potential measures to increase flood resilience related to critical infrastructure networks. Therefore, a more comprehensive approach is needed which helps accessing knowledge of actors in a structured way. Fort Lauderdale, Florida, United States has suffered from flood impacts, especially from disruptions in critical infrastructure. This paper shows how shared insight among different sectors and stakeholders into critical infrastructure resilience and potential resilience-enhancing measures was obtained using input from these actors. It also provides a first quantitative indication of resilience, indicated by the potential disruption due to floods and the effect of measures on resilience. The paper contributes to the existing literature on resilience specifically by considering the duration of disruption, the inclusion of critical infrastructure disruption in flood impact analysis, and the step from resilience quantification to measures.

We present here the analysis of 20 years of high-resolution experimental winter seasonal CLImate reForecasts for Florida (CLIFF). These winter seasonal reforecasts were dynamically downscaled by a regional atmospheric model at 10km grid spacing from a global model run at T62 spectral resolution (~210km grid spacing at the equator) forced with sea surface temperatures (SST) obtained from one of the global models in the North American Multimodel Ensemble (NMME). CLIFF was designed in consultation with water managers (in utilities and public water supply) in Florida targeting its five water management districts, including two smaller watersheds of two specific stakeholders in central Florida that manage public water supply. This enterprise was undertaken in an attempt to meet the climate forecast needs of water management in Florida.CLIFF has 30 ensemble members per season generated by changes to the physics and the lateral boundary conditions of the regional atmospheric model. Both deterministic and probabilistic skill measures of the seasonal precipitation at the zero-month lead for November-December-January (NDJ) and one-month lead for December-January-February (DJF) show that CLIFF has higher seasonal prediction skill than persistence. The results of the seasonal prediction skill of land surface temperature are more sobering than precipitation, although, in many instances, it is still better than the persistence skill.

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